Pillar Mothers: Perspective on the Adaptation Process of Mothers of Autistic Children
Bibliographic record
Abstract
Abstract Mothers of autistic children encounter numerous daily challenges that can affect their adaptation. While many studies have documented the impact on mothers of having an autistic child and factors contributing to their adaptation and their experiences of motherhood, few have examined how mothers of autistic children perceive their overall adaptation. We investigated with a qualitative design how mothers of autistic children perceive stressors, facilitators (resources, coping strategies, and contexts), and outcomes of adaptation in various life domains. Participants included 17 mothers of autistic children ranging from 2 to 8 years old. Mothers participated in a phone interview about their perception of their successes, challenges, and adaptation as mothers of their children. A thematic analysis was conducted on interview transcripts using inductive and deductive coding. A cross-case analysis was subsequently used to identify themes and subthemes. Results highlight the complexity of the maternal adaptation process in the context of autism, which starts before the child’s diagnosis. Stressors, facilitators, and outcomes were described as overlapping in the psychological, social, professional, marital, and parental life domains. The accumulation of stressors was identified as mothers of autistic children’s main source of stress and almost impossible to reduce. Participants explained having difficulties accessing effective facilitators. While outcomes of adaptation vary across mothers and life domains, indicators of distress were identified for all participants. Implications are discussed regarding how service providers and society could better support mothers of autistic children by considering their complex reality and by providing more resources and information.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".